{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "67e2adae",
   "metadata": {},
   "source": [
    "## 数据加载与处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "4f0ea612",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "plt.rcParams['font.family'] = 'Microsoft YaHei'\n",
    "plt.rcParams['font.size'] = 18"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25427bf6",
   "metadata": {},
   "source": [
    "### 男生数据处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "ee7ad3e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>男1000米跑</th>\n",
       "      <th>男1000米跑分数</th>\n",
       "      <th>男50米跑</th>\n",
       "      <th>男50米跑分数</th>\n",
       "      <th>男跳远</th>\n",
       "      <th>男跳远分数</th>\n",
       "      <th>男体前屈</th>\n",
       "      <th>男体前屈分数</th>\n",
       "      <th>男引体</th>\n",
       "      <th>男引体分数</th>\n",
       "      <th>男肺活量</th>\n",
       "      <th>男肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.16</td>\n",
       "      <td>70</td>\n",
       "      <td>7.70</td>\n",
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       "      <td>225</td>\n",
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       "      <td>52.700001</td>\n",
       "      <td>17.410000</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
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       "      <td>男</td>\n",
       "      <td>4.09</td>\n",
       "      <td>74</td>\n",
       "      <td>8.45</td>\n",
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       "      <td>218</td>\n",
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       "      <td>169</td>\n",
       "      <td>46.500000</td>\n",
       "      <td>16.280001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.21</td>\n",
       "      <td>68</td>\n",
       "      <td>8.05</td>\n",
       "      <td>74</td>\n",
       "      <td>206</td>\n",
       "      <td>64</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4946</td>\n",
       "      <td>100</td>\n",
       "      <td>183</td>\n",
       "      <td>79.699997</td>\n",
       "      <td>23.799999</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>3.44</td>\n",
       "      <td>85</td>\n",
       "      <td>7.52</td>\n",
       "      <td>78</td>\n",
       "      <td>210</td>\n",
       "      <td>66</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>9</td>\n",
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       "      <td>171</td>\n",
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       "      <td>50</td>\n",
       "      <td>8.76</td>\n",
       "      <td>66</td>\n",
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       "      <td>40</td>\n",
       "      <td>9.55</td>\n",
       "      <td>50</td>\n",
       "      <td>210</td>\n",
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       "      <td>15</td>\n",
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       "      <td>177</td>\n",
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       "      <td>24.260000</td>\n",
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       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>474</td>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>3.25</td>\n",
       "      <td>100</td>\n",
       "      <td>7.50</td>\n",
       "      <td>80</td>\n",
       "      <td>252</td>\n",
       "      <td>90</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
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       "      <td>100</td>\n",
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       "      <td>4.39</td>\n",
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       "      <td>7.81</td>\n",
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       "  </tbody>\n",
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       "<p>431 rows × 18 columns</p>\n",
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      ],
      "text/plain": [
       "     index  班级 性别  男1000米跑  男1000米跑分数  男50米跑  男50米跑分数  男跳远  男跳远分数  男体前屈  \\\n",
       "0        0   1  男     4.13         72   8.88       66  195     60    12   \n",
       "1        1   1  男     4.16         70   7.70       78  225     74    11   \n",
       "2        2   1  男     4.09         74   8.45       70  218     70    14   \n",
       "3        3   1  男     4.21         68   8.05       74  206     64    13   \n",
       "4        4   1  男     3.44         85   7.52       78  210     66    13   \n",
       "..     ...  .. ..      ...        ...    ...      ...  ...    ...   ...   \n",
       "426    470  17  男     3.54         80   7.51       78  238     80    13   \n",
       "427    471  17  男     4.58         50   8.76       66  200     62    12   \n",
       "428    473  17  男     5.19         40   9.55       50  210     66    15   \n",
       "429    474  17  男     3.25        100   7.50       80  252     90    13   \n",
       "430    475  17  男     4.39         62   7.81       76  208     66    14   \n",
       "\n",
       "     男体前屈分数  男引体  男引体分数  男肺活量  男肺活量分数   身高         体重        BMI  \n",
       "0        74    1      0  2785      62  170  72.599998  25.120001  \n",
       "1        74    7     60  3133      68  174  52.700001  17.410000  \n",
       "2        78    1      0  3901      80  169  46.500000  16.280001  \n",
       "3        76    1      0  4946     100  183  79.699997  23.799999  \n",
       "4        76    9     68  3538      74  171  54.700001  18.709999  \n",
       "..      ...  ...    ...   ...     ...  ...        ...        ...  \n",
       "426      76   11     76  5572     100  176  59.500000  19.209999  \n",
       "427      74    9     68  4533      95  169  51.299999  17.959999  \n",
       "428      80    6     50  7042     100  177  76.000000  24.260000  \n",
       "429      76   13     85  5755     100  181  65.000000  19.840000  \n",
       "430      78   11     76  5688     100  172  51.700001  17.480000  \n",
       "\n",
       "[431 rows x 18 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score_boy = pd.read_excel('./体测分数_男生.xls')\n",
    "# 删除缺考人员，所有成绩均为0的为缺考人员\n",
    "score_boy=score_boy[(score_boy[['男1000米跑','男50米跑','男跳远','男体前屈','男引体','男肺活量']]!=0).all(axis=1)]\n",
    "# 体侧分数基本不会有重复数据，但是不排除录入数据时重复录入，故需要做一次删除重复数据\n",
    "score_boy.drop_duplicates(inplace=True)\n",
    "score_boy.reset_index(inplace=True)\n",
    "score_boy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "b2c3f608",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>471</td>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>298</td>\n",
       "      <td>50</td>\n",
       "      <td>8.76</td>\n",
       "      <td>66</td>\n",
       "      <td>200</td>\n",
       "      <td>62</td>\n",
       "      <td>12</td>\n",
       "      <td>74</td>\n",
       "      <td>9</td>\n",
       "      <td>68</td>\n",
       "      <td>4533</td>\n",
       "      <td>95</td>\n",
       "      <td>169</td>\n",
       "      <td>51.299999</td>\n",
       "      <td>17.959999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>473</td>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>319</td>\n",
       "      <td>40</td>\n",
       "      <td>9.55</td>\n",
       "      <td>50</td>\n",
       "      <td>210</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>80</td>\n",
       "      <td>6</td>\n",
       "      <td>50</td>\n",
       "      <td>7042</td>\n",
       "      <td>100</td>\n",
       "      <td>177</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>24.260000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>474</td>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>205</td>\n",
       "      <td>100</td>\n",
       "      <td>7.50</td>\n",
       "      <td>80</td>\n",
       "      <td>252</td>\n",
       "      <td>90</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>13</td>\n",
       "      <td>85</td>\n",
       "      <td>5755</td>\n",
       "      <td>100</td>\n",
       "      <td>181</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>19.840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>475</td>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>279</td>\n",
       "      <td>62</td>\n",
       "      <td>7.81</td>\n",
       "      <td>76</td>\n",
       "      <td>208</td>\n",
       "      <td>66</td>\n",
       "      <td>14</td>\n",
       "      <td>78</td>\n",
       "      <td>11</td>\n",
       "      <td>76</td>\n",
       "      <td>5688</td>\n",
       "      <td>100</td>\n",
       "      <td>172</td>\n",
       "      <td>51.700001</td>\n",
       "      <td>17.480000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>431 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index  班级 性别  男1000米跑  男1000米跑分数  男50米跑  男50米跑分数  男跳远  男跳远分数  男体前屈  \\\n",
       "0        0   1  男      253         72   8.88       66  195     60    12   \n",
       "1        1   1  男      256         70   7.70       78  225     74    11   \n",
       "2        2   1  男      249         74   8.45       70  218     70    14   \n",
       "3        3   1  男      261         68   8.05       74  206     64    13   \n",
       "4        4   1  男      224         85   7.52       78  210     66    13   \n",
       "..     ...  .. ..      ...        ...    ...      ...  ...    ...   ...   \n",
       "426    470  17  男      234         80   7.51       78  238     80    13   \n",
       "427    471  17  男      298         50   8.76       66  200     62    12   \n",
       "428    473  17  男      319         40   9.55       50  210     66    15   \n",
       "429    474  17  男      205        100   7.50       80  252     90    13   \n",
       "430    475  17  男      279         62   7.81       76  208     66    14   \n",
       "\n",
       "     男体前屈分数  男引体  男引体分数  男肺活量  男肺活量分数   身高         体重        BMI  \n",
       "0        74    1      0  2785      62  170  72.599998  25.120001  \n",
       "1        74    7     60  3133      68  174  52.700001  17.410000  \n",
       "2        78    1      0  3901      80  169  46.500000  16.280001  \n",
       "3        76    1      0  4946     100  183  79.699997  23.799999  \n",
       "4        76    9     68  3538      74  171  54.700001  18.709999  \n",
       "..      ...  ...    ...   ...     ...  ...        ...        ...  \n",
       "426      76   11     76  5572     100  176  59.500000  19.209999  \n",
       "427      74    9     68  4533      95  169  51.299999  17.959999  \n",
       "428      80    6     50  7042     100  177  76.000000  24.260000  \n",
       "429      76   13     85  5755     100  181  65.000000  19.840000  \n",
       "430      78   11     76  5688     100  172  51.700001  17.480000  \n",
       "\n",
       "[431 rows x 18 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def convert_boy(x):\n",
    "    x = str(round(x,2))\n",
    "    x = x.split(\".\")\n",
    "    m=float(x[0])\n",
    "    s=float(x[1])\n",
    "    return int(m*60+s)\n",
    "# 男生成绩数据转换\n",
    "score_boy.iloc[:,3]=score_boy.iloc[:,3].apply(convert_boy)\n",
    "score_boy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c15f3223",
   "metadata": {},
   "source": [
    "### 女生数据处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "5f9ce7b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>女800米跑</th>\n",
       "      <th>女800米跑分数</th>\n",
       "      <th>女50米跑</th>\n",
       "      <th>女50米跑分数</th>\n",
       "      <th>女跳远</th>\n",
       "      <th>女跳远分数</th>\n",
       "      <th>女体前屈</th>\n",
       "      <th>女体前屈分数</th>\n",
       "      <th>女仰卧</th>\n",
       "      <th>女仰卧分数</th>\n",
       "      <th>女肺活量</th>\n",
       "      <th>女肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.22</td>\n",
       "      <td>100</td>\n",
       "      <td>9.32</td>\n",
       "      <td>72</td>\n",
       "      <td>185</td>\n",
       "      <td>85</td>\n",
       "      <td>16</td>\n",
       "      <td>76</td>\n",
       "      <td>48</td>\n",
       "      <td>85</td>\n",
       "      <td>3775</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>51.299999</td>\n",
       "      <td>19.309999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>4.59</td>\n",
       "      <td>40</td>\n",
       "      <td>11.44</td>\n",
       "      <td>10</td>\n",
       "      <td>148</td>\n",
       "      <td>60</td>\n",
       "      <td>9</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>66</td>\n",
       "      <td>3683</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>66.599998</td>\n",
       "      <td>25.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.46</td>\n",
       "      <td>80</td>\n",
       "      <td>13.40</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>7</td>\n",
       "      <td>64</td>\n",
       "      <td>40</td>\n",
       "      <td>76</td>\n",
       "      <td>3331</td>\n",
       "      <td>100</td>\n",
       "      <td>157.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>24.340000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.39</td>\n",
       "      <td>85</td>\n",
       "      <td>9.52</td>\n",
       "      <td>70</td>\n",
       "      <td>172</td>\n",
       "      <td>76</td>\n",
       "      <td>21</td>\n",
       "      <td>90</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>3701</td>\n",
       "      <td>100</td>\n",
       "      <td>160.0</td>\n",
       "      <td>50.700001</td>\n",
       "      <td>19.799999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.43</td>\n",
       "      <td>80</td>\n",
       "      <td>9.79</td>\n",
       "      <td>68</td>\n",
       "      <td>145</td>\n",
       "      <td>50</td>\n",
       "      <td>8</td>\n",
       "      <td>64</td>\n",
       "      <td>34</td>\n",
       "      <td>70</td>\n",
       "      <td>3592</td>\n",
       "      <td>100</td>\n",
       "      <td>167.0</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>22.910000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556</th>\n",
       "      <td>588</td>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>3.51</td>\n",
       "      <td>78</td>\n",
       "      <td>9.60</td>\n",
       "      <td>68</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>24</td>\n",
       "      <td>95</td>\n",
       "      <td>41</td>\n",
       "      <td>78</td>\n",
       "      <td>2255</td>\n",
       "      <td>70</td>\n",
       "      <td>158.0</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>19.629999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557</th>\n",
       "      <td>589</td>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.00</td>\n",
       "      <td>76</td>\n",
       "      <td>10.18</td>\n",
       "      <td>64</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>13</td>\n",
       "      <td>72</td>\n",
       "      <td>36</td>\n",
       "      <td>72</td>\n",
       "      <td>2937</td>\n",
       "      <td>85</td>\n",
       "      <td>161.0</td>\n",
       "      <td>55.700001</td>\n",
       "      <td>21.490000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>590</td>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>3.45</td>\n",
       "      <td>80</td>\n",
       "      <td>10.18</td>\n",
       "      <td>64</td>\n",
       "      <td>152</td>\n",
       "      <td>62</td>\n",
       "      <td>15</td>\n",
       "      <td>76</td>\n",
       "      <td>35</td>\n",
       "      <td>72</td>\n",
       "      <td>2592</td>\n",
       "      <td>76</td>\n",
       "      <td>165.0</td>\n",
       "      <td>48.599998</td>\n",
       "      <td>17.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>591</td>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.01</td>\n",
       "      <td>74</td>\n",
       "      <td>9.67</td>\n",
       "      <td>68</td>\n",
       "      <td>165</td>\n",
       "      <td>70</td>\n",
       "      <td>10</td>\n",
       "      <td>68</td>\n",
       "      <td>41</td>\n",
       "      <td>78</td>\n",
       "      <td>1829</td>\n",
       "      <td>60</td>\n",
       "      <td>154.0</td>\n",
       "      <td>43.599998</td>\n",
       "      <td>18.379999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560</th>\n",
       "      <td>592</td>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.48</td>\n",
       "      <td>50</td>\n",
       "      <td>9.09</td>\n",
       "      <td>74</td>\n",
       "      <td>180</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>68</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>2962</td>\n",
       "      <td>85</td>\n",
       "      <td>162.0</td>\n",
       "      <td>55.299999</td>\n",
       "      <td>21.070000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>561 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index  班级 性别  女800米跑  女800米跑分数  女50米跑  女50米跑分数  女跳远  女跳远分数  女体前屈  女体前屈分数  \\\n",
       "0        0   1  女    3.22       100   9.32       72  185     85    16      76   \n",
       "1        1   1  女    4.59        40  11.44       10  148     60     9      66   \n",
       "2        2   1  女    3.46        80  13.40        0  150     60     7      64   \n",
       "3        3   1  女    3.39        85   9.52       70  172     76    21      90   \n",
       "4        4   1  女    3.43        80   9.79       68  145     50     8      64   \n",
       "..     ...  .. ..     ...       ...    ...      ...  ...    ...   ...     ...   \n",
       "556    588  17  女    3.51        78   9.60       68  150     60    24      95   \n",
       "557    589  17  女    4.00        76  10.18       64  150     60    13      72   \n",
       "558    590  17  女    3.45        80  10.18       64  152     62    15      76   \n",
       "559    591  17  女    4.01        74   9.67       68  165     70    10      68   \n",
       "560    592  17  女    4.48        50   9.09       74  180     80    10      68   \n",
       "\n",
       "     女仰卧  女仰卧分数  女肺活量  女肺活量分数     身高         体重        BMI  \n",
       "0     48     85  3775     100  163.0  51.299999  19.309999  \n",
       "1     29     66  3683     100  163.0  66.599998  25.070000  \n",
       "2     40     76  3331     100  157.0  60.000000  24.340000  \n",
       "3     46     85  3701     100  160.0  50.700001  19.799999  \n",
       "4     34     70  3592     100  167.0  63.900002  22.910000  \n",
       "..   ...    ...   ...     ...    ...        ...        ...  \n",
       "556   41     78  2255      70  158.0  49.000000  19.629999  \n",
       "557   36     72  2937      85  161.0  55.700001  21.490000  \n",
       "558   35     72  2592      76  165.0  48.599998  17.850000  \n",
       "559   41     78  1829      60  154.0  43.599998  18.379999  \n",
       "560   46     85  2962      85  162.0  55.299999  21.070000  \n",
       "\n",
       "[561 rows x 18 columns]"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score_girl = pd.read_excel('./体测分数_女生.xls')\n",
    "# 删除缺考人员，所有成绩均为0的为缺考人员\n",
    "score_girl=score_girl[(score_girl[['女800米跑','女50米跑','女跳远','女体前屈','女仰卧','女肺活量']]!=0).all(axis=1)]\n",
    "# 体侧分数基本不会有重复数据，但是不排除录入数据时重复录入，故需要做一次删除重复数据\n",
    "score_girl.drop_duplicates(inplace=True)\n",
    "score_girl=score_girl[score_girl['女800米跑']<100]\n",
    "score_girl.reset_index(inplace=True)\n",
    "score_girl\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "ded0adbc",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>女800米跑</th>\n",
       "      <th>女800米跑分数</th>\n",
       "      <th>女50米跑</th>\n",
       "      <th>女50米跑分数</th>\n",
       "      <th>女跳远</th>\n",
       "      <th>女跳远分数</th>\n",
       "      <th>女体前屈</th>\n",
       "      <th>女体前屈分数</th>\n",
       "      <th>女仰卧</th>\n",
       "      <th>女仰卧分数</th>\n",
       "      <th>女肺活量</th>\n",
       "      <th>女肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>202</td>\n",
       "      <td>100</td>\n",
       "      <td>9.32</td>\n",
       "      <td>72</td>\n",
       "      <td>185</td>\n",
       "      <td>85</td>\n",
       "      <td>16</td>\n",
       "      <td>76</td>\n",
       "      <td>48</td>\n",
       "      <td>85</td>\n",
       "      <td>3775</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>51.299999</td>\n",
       "      <td>19.309999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>299</td>\n",
       "      <td>40</td>\n",
       "      <td>11.44</td>\n",
       "      <td>10</td>\n",
       "      <td>148</td>\n",
       "      <td>60</td>\n",
       "      <td>9</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>66</td>\n",
       "      <td>3683</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>66.599998</td>\n",
       "      <td>25.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>226</td>\n",
       "      <td>80</td>\n",
       "      <td>13.40</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>7</td>\n",
       "      <td>64</td>\n",
       "      <td>40</td>\n",
       "      <td>76</td>\n",
       "      <td>3331</td>\n",
       "      <td>100</td>\n",
       "      <td>157.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>24.340000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>219</td>\n",
       "      <td>85</td>\n",
       "      <td>9.52</td>\n",
       "      <td>70</td>\n",
       "      <td>172</td>\n",
       "      <td>76</td>\n",
       "      <td>21</td>\n",
       "      <td>90</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>3701</td>\n",
       "      <td>100</td>\n",
       "      <td>160.0</td>\n",
       "      <td>50.700001</td>\n",
       "      <td>19.799999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>223</td>\n",
       "      <td>80</td>\n",
       "      <td>9.79</td>\n",
       "      <td>68</td>\n",
       "      <td>145</td>\n",
       "      <td>50</td>\n",
       "      <td>8</td>\n",
       "      <td>64</td>\n",
       "      <td>34</td>\n",
       "      <td>70</td>\n",
       "      <td>3592</td>\n",
       "      <td>100</td>\n",
       "      <td>167.0</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>22.910000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556</th>\n",
       "      <td>588</td>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>231</td>\n",
       "      <td>78</td>\n",
       "      <td>9.60</td>\n",
       "      <td>68</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>24</td>\n",
       "      <td>95</td>\n",
       "      <td>41</td>\n",
       "      <td>78</td>\n",
       "      <td>2255</td>\n",
       "      <td>70</td>\n",
       "      <td>158.0</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>19.629999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557</th>\n",
       "      <td>589</td>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>240</td>\n",
       "      <td>76</td>\n",
       "      <td>10.18</td>\n",
       "      <td>64</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>13</td>\n",
       "      <td>72</td>\n",
       "      <td>36</td>\n",
       "      <td>72</td>\n",
       "      <td>2937</td>\n",
       "      <td>85</td>\n",
       "      <td>161.0</td>\n",
       "      <td>55.700001</td>\n",
       "      <td>21.490000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>590</td>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>225</td>\n",
       "      <td>80</td>\n",
       "      <td>10.18</td>\n",
       "      <td>64</td>\n",
       "      <td>152</td>\n",
       "      <td>62</td>\n",
       "      <td>15</td>\n",
       "      <td>76</td>\n",
       "      <td>35</td>\n",
       "      <td>72</td>\n",
       "      <td>2592</td>\n",
       "      <td>76</td>\n",
       "      <td>165.0</td>\n",
       "      <td>48.599998</td>\n",
       "      <td>17.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>591</td>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>241</td>\n",
       "      <td>74</td>\n",
       "      <td>9.67</td>\n",
       "      <td>68</td>\n",
       "      <td>165</td>\n",
       "      <td>70</td>\n",
       "      <td>10</td>\n",
       "      <td>68</td>\n",
       "      <td>41</td>\n",
       "      <td>78</td>\n",
       "      <td>1829</td>\n",
       "      <td>60</td>\n",
       "      <td>154.0</td>\n",
       "      <td>43.599998</td>\n",
       "      <td>18.379999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560</th>\n",
       "      <td>592</td>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>288</td>\n",
       "      <td>50</td>\n",
       "      <td>9.09</td>\n",
       "      <td>74</td>\n",
       "      <td>180</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>68</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>2962</td>\n",
       "      <td>85</td>\n",
       "      <td>162.0</td>\n",
       "      <td>55.299999</td>\n",
       "      <td>21.070000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>561 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index  班级 性别  女800米跑  女800米跑分数  女50米跑  女50米跑分数  女跳远  女跳远分数  女体前屈  女体前屈分数  \\\n",
       "0        0   1  女     202       100   9.32       72  185     85    16      76   \n",
       "1        1   1  女     299        40  11.44       10  148     60     9      66   \n",
       "2        2   1  女     226        80  13.40        0  150     60     7      64   \n",
       "3        3   1  女     219        85   9.52       70  172     76    21      90   \n",
       "4        4   1  女     223        80   9.79       68  145     50     8      64   \n",
       "..     ...  .. ..     ...       ...    ...      ...  ...    ...   ...     ...   \n",
       "556    588  17  女     231        78   9.60       68  150     60    24      95   \n",
       "557    589  17  女     240        76  10.18       64  150     60    13      72   \n",
       "558    590  17  女     225        80  10.18       64  152     62    15      76   \n",
       "559    591  17  女     241        74   9.67       68  165     70    10      68   \n",
       "560    592  17  女     288        50   9.09       74  180     80    10      68   \n",
       "\n",
       "     女仰卧  女仰卧分数  女肺活量  女肺活量分数     身高         体重        BMI  \n",
       "0     48     85  3775     100  163.0  51.299999  19.309999  \n",
       "1     29     66  3683     100  163.0  66.599998  25.070000  \n",
       "2     40     76  3331     100  157.0  60.000000  24.340000  \n",
       "3     46     85  3701     100  160.0  50.700001  19.799999  \n",
       "4     34     70  3592     100  167.0  63.900002  22.910000  \n",
       "..   ...    ...   ...     ...    ...        ...        ...  \n",
       "556   41     78  2255      70  158.0  49.000000  19.629999  \n",
       "557   36     72  2937      85  161.0  55.700001  21.490000  \n",
       "558   35     72  2592      76  165.0  48.599998  17.850000  \n",
       "559   41     78  1829      60  154.0  43.599998  18.379999  \n",
       "560   46     85  2962      85  162.0  55.299999  21.070000  \n",
       "\n",
       "[561 rows x 18 columns]"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def convert_girl(x):\n",
    "    x = str(round(x,2))\n",
    "    x = x.split(\".\")\n",
    "    m=float(x[0])\n",
    "    s=float(x[1])\n",
    "    return int(m*60+s)\n",
    "# 女生成绩数据转换\n",
    "score_girl.iloc[:,3]=score_girl.iloc[:,3].apply(convert_girl)\n",
    "score_girl"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "397ed85e",
   "metadata": {},
   "source": [
    "## 数据可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a818c363",
   "metadata": {},
   "source": [
    "### 男生1000m成绩可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "078a09e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_boy_1000m=pd.cut(score_boy.男1000米跑,#分箱数据\n",
    "bins = [136,211,286,361],#分箱断点\n",
    "right = False,# 左闭右开\n",
    "labels=['不及格','及格','满分']).value_counts()# 分箱后分类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "c0def7ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,9))\n",
    "_ = plt.pie(num_boy_1000m,labels=num_boy_1000m.index,autopct='%0.2f%%',\n",
    "       wedgeprops=dict(linewidth=3,width=0.5),pctdistance=0.8,\n",
    "       textprops=dict(fontsize=20))\n",
    "_ = plt.title(label='男1000米成绩分布情况',\n",
    "             fontsize=32,weight='bold',\n",
    "             color='white',backgroundcolor='#c5b783')\n",
    "plt.savefig('./男1000米成绩分布情况.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11c29c31",
   "metadata": {},
   "source": [
    "### 男生引体向上成绩可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "aa3108d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_boy_pullUp=pd.cut(score_boy.男引体,#分箱数据\n",
    "bins = [0,8,16,24],#分箱断点\n",
    "right = False,# 左闭右开\n",
    "labels=['不及格','及格','满分']).value_counts()# 分箱后分类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "ec379a4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,9))\n",
    "_ = plt.pie(num_boy_pullUp,labels=num_boy_pullUp.index,autopct='%0.2f%%',\n",
    "       wedgeprops=dict(linewidth=3,width=0.5),pctdistance=0.8,\n",
    "       textprops=dict(fontsize=20))\n",
    "_ = plt.title(label='男引体向上成绩分布情况',\n",
    "             fontsize=32,weight='bold',\n",
    "             color='white',backgroundcolor='#c5b783')\n",
    "plt.savefig('./男引体向上成绩分布情况.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0737f2be",
   "metadata": {},
   "source": [
    "### 女生800m成绩可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "5935e2fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,9))\n",
    "plt.hist(score_girl['女800米跑'],bins=4,rwidth=1)\n",
    "_ = plt.xticks([150,210,270,330])\n",
    "_1 = plt.title(label='女生800m成绩分布情况',\n",
    "             fontsize=32,weight='bold',pad=30,\n",
    "             color='white',backgroundcolor='#c5b783')\n",
    "plt.savefig('./女生800m成绩分布情况.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83808072",
   "metadata": {},
   "source": [
    "### 女生跳远成绩可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "cba32d04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,9))\n",
    "_ = plt.hist(score_girl['女跳远'],[90,130,170,210,250],\n",
    "             histtype='bar', rwidth=1)\n",
    "_1 = plt.title(label='女生跳远成绩分布情况',\n",
    "             fontsize=32,weight='bold',pad=30,\n",
    "             color='white',backgroundcolor='#c5b783')\n",
    "plt.savefig('./女生800m成绩分布情况.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f08c63b3",
   "metadata": {},
   "source": [
    "### 男女生体重比例统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "7f54d125",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "正常     0.791183\n",
       "超重     0.120650\n",
       "肥胖     0.064965\n",
       "低体重    0.023202\n",
       "Name: BMI, dtype: float64"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BMI_boy = pd.cut(score_boy['BMI'].round(1),\n",
    "                 bins = [0,16.4,23.3,26.4,50],\n",
    "                 right = False,\n",
    "                 labels=['低体重','正常','超重','肥胖']).value_counts()\n",
    "BMI_boy_per = BMI_boy/BMI_boy.sum()\n",
    "BMI_boy_per"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "874f1a82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "正常     0.752228\n",
       "超重     0.146168\n",
       "肥胖     0.085561\n",
       "低体重    0.016043\n",
       "Name: BMI, dtype: float64"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BMI_girl= pd.cut(score_girl['BMI'].round(1),\n",
    "                 bins = [0,16.5,22.8,25.3,50],\n",
    "                 right = False,\n",
    "                 labels=['低体重','正常','超重','肥胖']).value_counts()\n",
    "BMI_girl_per = BMI_girl/BMI_girl.sum()\n",
    "BMI_girl_per"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "8f95a79d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,12))\n",
    "plt.pie(BMI_boy_per,radius=1,\n",
    "        autopct='%0.2f%%',\n",
    "        pctdistance=0.85,\n",
    "        labels = ['低体重','正常','超重','肥胖'],\n",
    "        colors= ['cyan','lime','yellow','tomato'],\n",
    "        wedgeprops={'linewidth':5,\n",
    "                    'width':0.5, \n",
    "                    'edgecolor':'white'},\n",
    "        textprops={'fontsize':18})\n",
    "_ = plt.pie(BMI_girl_per,\n",
    "        radius=0.6,\n",
    "        autopct='%0.2f%%',\n",
    "        pctdistance=0.6,\n",
    "        colors= ['cyan','lime','yellow','tomato'],\n",
    "        wedgeprops={'linewidth':5,\n",
    "                    'width':0.6,\n",
    "                    'edgecolor':'white'},\n",
    "        textprops={'fontsize':18})\n",
    "plt.legend(['低体重','正常','超重','肥胖'],loc = 'upper right',bbox_to_anchor = (0.65,0,0.4,1),title = 'BMI')\n",
    "_1 = plt.title(label='男女生体重指数比例统计',\n",
    "             fontsize=32,weight='bold',pad=30,\n",
    "             color='white',backgroundcolor='#c5b783')\n",
    "plt.savefig('./男女生体重指数比例统计.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "68a6893f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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